Ejection fraction is a quantitative way of assessing overall cardiac function. A low ejection fraction can indicate a number of diseases. Quantitative methods of assessing ejection fraction generally require the use of multiple ultrasound planes and edge detection. One accepted technique is to acquire images in orthogonal planes for each heart chamber to be assessed. Tracings of the outline of the chamber in the orthogonal images are used to estimate the chamber volume by assuming an elliptical shape for each image depth. By estimating the volume of the chamber at end of diastole ("ED") and end of systole ("ES"), the ejection fraction can be calculated using the following relation: Ejection Fraction=[1-(Volume at ES)/Volume at ED)]. With a two-dimensional scanner, this technique can be made semi-automatic by automatically detecting the border of the chamber from selected sequences from orthogonal planes and performing the necessary numerical integrations online. This technique can be improved by using additional planes and eliminating the assumption that the heart cross section is elliptical. Because of the required orientation and calculation, this is generally considered only in three-dimensional imaging.
Because this quantitative method requires that volumes be determined, the method functions poorly when the entire heart chamber is poorly visualized. Hypoechoic and anisotropic endocardium and myocardium have long made it difficult to determine the boundary of the heart, especially with hard-to-image patients. In many cases, the boundary of the chamber must be estimated because the endocardium is not visible. Ultrasound contrast agents improve cardiac chamber edge detection, and left ventricular opacification with contrast agents improves ejection fraction measurements using manual or automatic techniques. However, the three-dimensional shape of the heart must still be acquired either through three-dimensional imaging or from assumptions based on orthogonal planes.
Because of the inaccuracy of the manual technique and the low availability of the automated three-dimensional technique, ejection fraction is commonly estimated by eye. In practice, an experienced clinician can generate a number to describe a qualitative assessment of heart function based on viewing several sets of images. This produces an ejection fraction percentage that is widely used in describing heart function and determining treatment. Although assessment of ejection fraction by eye is accepted, scientific physicians prefer to have a truly quantitative method of generating this number. This desire drives the application of edge detection algorithms in cardiology as well as serving as a clinical rational for three-dimensional imaging.
There is a need, therefore, for an improved method for assessing ejection fraction.